Biometric identification and control systems and methods for providing customizable security through authentication of biosignal representations of one or more user-specific and user-selected gesture-intentions

ABSTRACT

In various aspects, systems and methods are described for a biometric identification and control for providing customizable security through authentication of biosignal representations and control. The biometric identification and control systems and methods comprise hardware and software components that are used to detect, via a biometric detection device, biometric signals of a user. These biosignals are analyzed by a processor communicatively coupled to the biometric detection device. After analyzation of the biosignals, a biometric profile is created and used with a security interface to access a secure resource or device or to output a command to another device.

FIELD OF THE DISCLOSURE

The present disclosure generally relates to biometric security, and,more particularly to biometric identification and control systems andmethods for providing customizable security through authentication ofbiosignal representations of one or more user-specific and user-selectedgesture-intentions.

BACKGROUND

As technology becomes more integrated into our everyday lives, theimportance for security becomes greater. Traditional methods of passwordprotection are slowly becoming antiquated due to new biometric scanners,such as seen on cellphones as thumbprint scanners. Current widely usedforms of security authentication lack high level security. Passwords andcodes can be hacked, guessed, or forgotten, and can be time intensive toenter. In addition, conventional methods for security to unlock physicalobjects, such as a door, typically involve using a lock and key.However, this method has drawbacks. For example, a key must always becarried. This causes the potential for keys to be lost, stolen, orcopied.

For the foregoing reasons, there is a need for enhanced security thatcan be administered by an authenticated user only. More specifically,there is a need for biometric identification and control systems andmethods for providing customizable security through authentication ofbiosignal representations of one or more user-specific and user-selectedgesture-intentions, as described herein.

BRIEF SUMMARY

The disclosed invention herein eliminates these problems through novelsystems and methods of authentication and security protection. Thedisclosure herein describes biometric identification and control systemsand methods that use voluntary biometric signals of a user forauthentication, providing a low, if not impossible, likelihood of theuser's unique biometric signals being replicated. For example, it wouldbe difficult, if not impossible, for hacker or thief to recreate thespecific biometric signals of a particular user, even if the hacker orthief knew a given user-specific and user-selected gesture-intention ofa user as described herein. In comparison, keys (e.g., hardware keys orcomputer security keys) can be copied or stolen, and locks can be pickedor hacked, all of which demonstrate a vulnerable and lower level ofsecurity.

Personal security, as described herein, and which is unique and specificto a given user, can be accomplished using voluntary biometric signals.For example, every tissue in the body is electrically active, creatingsmall levels of electricity when used or even when idle. Much like afingerprint, these levels of electricity are completely unique to eachuser. These patterns of signals can take many different forms and bemeasured through various means, such as electromyography,electrocardiography, infrared, ultrasound, photodiodes, accelerometers,and gyroscopes. These biometric signals also differ if a user performs aspecific motion. For example, making a first or doing a “thumbs-up”motion or gesture, and/or an “okay” motion or gesture, would createdifferent biometric signals, which would be unique to the user. If afirst user were to perform the exact same motion as a second user, thenthe first user would produce a different pattern of biometric signalsthan the second user. The unique biometric signal patterns can be usedfor security authentication and executing commands, especially when usedin combination of voluntary signals that can only be created by anauthenticated user. The user will be able to execute these commandssimply by performing a voluntary action, recreating their unique set ofvoluntary biometric signals, thereby enabling biometric authenticationbased on not only their unique gestures, but also their unique biometricsignals creates by those unique gestures. Additionally, oralternatively, voluntary actions may also be performed in sequence formore advanced security measures, such as: making a fist, followed by athumbs up, followed by a wave, etc.

Accordingly, a need for the invention arises from the necessity ofrequiring a technology that allows rapid security authentication andexecution of commands in relation to voluntary biometric signals thatare uniquely generated by a user. These biometric signals are specificto a single user (based on his or her own generated biometric signals byhis or her muscles or groups of muscles), which therefore can be used toprovide a unique and high level of security on a per-user basis.

A need for the invention also arises from the necessity of requiring atechnology that allows for enhanced personal security, and through thenecessity of requiring a single technology that can conduct biometricauthentication for one or many secure resources or devices, as describedherein.

Various embodiments of the present disclosure are described hereinregarding identifying and/or categorizing voluntary movement biometricsignals to provide security based on biometric signals. Such embodimentsmay include collecting and analyzing voluntarily-generated biometricdata, using the analyzed data to authenticate the user and/or executesoftware and hardware commands, and/or creating biometric profiles andcustomizable commands to facilitate enhanced security. A need forembodiments of the of the present disclosure arises from the necessityof having a method to rapidly detect biometric signals from a user andcategorize signals as voluntary, and upon subsequent comparison with asecond set of biometric data, performing a security operation aspredetermined by the user. The embodiments as described herein describebiometric systems and methods that allow a user to quickly categorizevoluntary movements for controlling access to secure resource(s) ordevice(s), which can include third party devices. In one or moreembodiments, during a given data collection session, the collection ofbiometric data from the user may guide a user through the process ofgenerating voluntary biometric data. The system may then providefeedback on the data collected, before storing the data as a first setof biometric data for a voluntary motion for that user. In variousembodiments, when the user conducts a voluntary motion, the system andmethods describe herein may receive voluntary motion data and compare itto the first set of voluntary biometric data, upon substantialsimilarity between data sets, performing a security authenticationprogram that may be coupled to a secure resource or device, such as athird party device or program.

In still further embodiments, a biometric identification and controlsystem is described. The biometric identification and control system isconfigured to provide customizable security through authentication ofbiosignal representations of one or more user-specific and user-selectedgesture-intentions. The biometric identification and control systemcomprises a biometric detection device configured to detect biometricsignal data of a user. The biometric identification and control systemfurther comprises a processor communicatively coupled to the biometricdetection device. The biometric identification and control systemfurther comprises a biometric software component comprising computinginstructions executable by the processor. Execution of the computinginstructions by the processor causes the processor to perform ananalysis of the biometric signal data of the user as detected by thebiometric detection device. In addition, execution of the computinginstructions by the processor causes the processor to create a biometricprofile based on the analysis of the biometric signal data. In variousembodiments, the biometric profile comprises an electronic recording ofa biosignal representation of a user-specific and user-selectedgesture-intention of the user. In addition, execution of the computinginstructions by the processor causes the processor to bind theuser-specific and user-selected gesture-intention of the user to asecurity interface. The security interface is operable to provideauthentication of the user for access to a secure resource or device.

In additional embodiments, a biometric identification and control methodis described regarding providing customizable security throughauthentication of biosignal representations of one or more user-specificand user-selected gesture-intentions. The biometric identification andcontrol method comprises performing, by a biometric software componentexecuted by a processor communicatively coupled to a biometric detectiondevice, an analysis of biometric signal data of a user as detected bythe biometric detection device. The biometric identification and controlmethod further comprises creating, by the biometric software component,a biometric profile based on the analysis of the biometric signal data.The biometric profile comprises an electronic recording of a biosignalrepresentation of a user-specific and user-selected gesture-intention ofthe user. The biometric identification and control method furthercomprises binding, by the biometric software component, theuser-specific and user-selected gesture-intention of the user to asecurity interface. The security interface is operable to provideauthentication of the user for access to a secure resource or device.

In still further embodiments, a tangible, non-transitorycomputer-readable medium stores instructions for providing customizablesecurity through authentication of biosignal representations of one ormore user-specific and user-selected gesture-intentions. Theinstructions, when executed by one or more processors, cause the one ormore processors to perform, by a biometric software component executedby a processor communicatively coupled to a biometric detection device,an analysis of biometric signal data of a user as detected by thebiometric detection device. The instructions, when executed by one ormore processors, further cause the one or more processors to create, bythe biometric software component, a biometric profile based on theanalysis of the biometric signal data. The biometric profile comprisesan electronic recording of a biosignal representation of a user-specificand user-selected gesture-intention of the user. The instructions, whenexecuted by one or more processors, further cause the one or moreprocessors to bind, by the biometric software component, theuser-specific and user-selected gesture-intention of the user to asecurity interface. The security interface is operable to provideauthentication of the user for access to a secure resource or device.

The representative embodiments of the present invention provide numerousadvantages over commonly used methods for providing biometric securityand detection of biometric signals. The general purpose of the inventionis to provide a method for highly secure, accurate, yet simple andquick, biometric authentication for a user that may be completed throughthe voluntary generation of biometric signals. In various embodiments,the many novel features described result in a new method for determiningthe identify of a user and authenticating the use of a secure resourceor device (e.g., a third party device) through a successful match orotherwise detection of voluntary biometric data as generated by theuser.

In various embodiments, a user may perform a gesture or gestureintention and the system may then detect and analyze the biometricsignals produced. Additionally, or alternatively, the systems and/ormethods described herein may store, e.g., in a memory, the biometricsignals and/or pattern of signals as a key or otherwise anauthentication key. The systems and/or methods may then analyze theuser's biometric signals for a second pattern of signals. If the secondanalyzed pattern is the same as the first analyzed pattern, then thesystem may authenticate the user and perform the intended command. Thiscan be hardware or software command and both thegesture/gesture-intention and the command output can be customizable. Ifa second analyzed pattern is not the same as the first analyzed pattern,then the device does not authenticate the user and the user will not beable to access the system or execute the intended command.

As described herein, the present invention generally comprises abiometric collection and authentication system configured to providecustomizable security through comparison of biometric signalrepresentations of one or more user-specific and user-selectedgesture-intentions. The biometric signals are identified by a biometricdetection device. A processor is communicatively coupled to thebiometric detection device and performs and analysis of the biometricsignal data of the user and executes computing instructions. Thesecomputing instructions cause the device to perform an analysis of thebiometric signal data detected form the user, and create a biometricprofile based on the biometric signal data related to a user's voluntarygesture or gesture intention. The biometric profile is used to provideauthentication of the user for access to a secure resource or device orto communicate computer commands to another device.

This biometric and identification control system may further comprise auser interface that allows the user to customize the security interfacein accordance with the user's selected voluntary gesture or selectedgesture-intentions. This user interface can be comprised of a tactilebased, auditory, or a virtual based user interface. The user interfaceis used to create customized software commands, calibrate user-specificgestures and gesture-intentions, and manage the biometric detectiondevice. The user interface can be used to manage the power, gestures,commands, and/or other settings of the biometric detection device.

The authenticating of a user's specific and selected gestures andgesture-intentions may further be comprised of collecting a first set ofuser biometric data and creating a biometric profile, then collecting asecond set of user biometric data and comparing to the first set ofbiometric data in order to authenticate the user as a function ofbiometric signal data.

The biometric signals that are detected can be made of eccentric,concentric, or isometric contraction of one or more muscles and/ormuscle groups. In some embodiments, these biometric signals are detectedthrough one or more electromyograph electrodes, electrocardiogramelectrodes, photodiodes (photoreceptors), ultrasound sensors (e.g.,ultrasound transducers), accelerometers, and/or gyroscopes.

The analysis of biometric signal data of the user may be used to createat least one unique key for the user. Such biometric signals may beanalyzed through fuzzy logic, pattern classification, computationalneural networks, forward dynamic modeling, and/or support vectormachines. The unique key or keys may be stored in a memory. The key maybe used for security authentication to allow or deny a user access to adevice and/or execute customized software programs.

Customized software commands, as descried herein, provide binding and/orlinking a function, as implemented by a processor of a biometric andidentification control system, to one or more gestures (e.g., alsodescribed herein as user-specific and user-selected gesture-intentions)of a user that is to be executed by the processor upon a user initiatingthose one or more gestures. The customized software function may alsoinclude a security authentication to lock or unlock an object, toinitiate a third party mechanically automated process, hardwarecomponent, and or initiate a software program.

In some embodiments, a user voluntary gesture (i.e., a user-specific anduser-selected gesture-intention) can be defined by, or selected from, alist of predetermined gestures. Additionally, or alternatively, a uservoluntary gesture (i.e., a user-specific and user-selectedgesture-intention) can be a unique voluntary gesture that is defined byor simply performed by the user.

In various embodiments, a biometric detection and identification controlsystem can be any combination of a wearable, implantable, and/or aremote device. The components for the detection of biometric signals canbe in contact with the user, subcutaneously positioned to the user,implanted within the user, or within proximity to the user.

The biometric identification and control system may comprise an adaptivelearning component that is configured to identify user-specific anduser-selected gesture-intention(s) based on collected or detectedbiosignals. These biosignals may be analyzed using a pattern recognitioncomponent that allows the addition or removal of biometric feedback datato optimize the adaptive learning component.

In some embodiments, digital recording of a biometric profile candefines a first and second user-specific and user-selectedgesture-intention of the user. In such embodiments, the seconduser-specific and user-selected gesture-intention may be recorded in asequence with the user-specific and user-selected gesture-intention ofthe user. The sequence may then be bound to a security interface and maybe required to provide authentication of the user for access to thesecure resource or device.

In various embodiments, a user-specific and user-selectedgesture-intention corresponds to a user-specific and user-selectedgesture-intention of the user where an actuated voluntary gesture is aresulting physical response of the user initiated upon performance ofthe user-specific and user-selected gesture-intention.

In some embodiments, a biometric profile may further comprises a secondelectronic recording of a second biosignal representation of the user.The second biosignal representation may either be deliberately not boundto the security interface or filtered by the processor to prevent accessto the security interface.

In accordance with the above, and with the disclosure herein, thepresent disclosure includes improvements in computer functionality or inimprovements to other technologies at least because the presentdisclosure recites that, e.g., a computing device, such as a wearablecomputing device, is enhanced via the biometric software or othercomponents herein that allow for enhanced security and/or authenticationof the computing or wearable device itself or via interfacing with othercomputing devices to provide or implement increased security viabiometric signals. That is, the present disclosure describesimprovements in the functioning of the computer itself or “any othertechnology or technical field” because a computing device, such aswearable, can be updated or enhanced to provide authentication and/oraccess to secure resource(s) and/or device(s), which can includereal-world objects such as doors and lock screens and the like. Thisimproves over the prior art at least because the systems and methodsherein provide for a faster and/or more secure way of accessing suchsecure resource(s) and/or device(s).

The present disclosure relates to improvement to other technologies ortechnical fields at least because the present disclosure relates to thefield of security and authentication, wherein, in the present inventionallows a wearable device to unlock or otherwise provide access toreal-world objects, including physical objects (e.g., mechanical locksand door) and/or computing resources (e.g., computers and laptops viareplacing traditional password login with a biometric login using auser's user-specific and user-selected gesture-intention).

In addition, the present disclosure includes applying certain aspects orfeatures, as described herein, with, or by use of, a particular machine,e.g., a wearable device or other similar device to provideauthentication of the user for access to a secure resource or device.

The present disclosure includes effecting a transformation or reductionof a particular article to a different state or thing, e.g.,transformation or reduction of biometric signals of a user toauthentication and security output used to provide authentication of theuser for access to a secure resource or device

The present disclosure includes specific features other than what iswell-understood, routine, conventional activity in the field, or addingunconventional steps that confine the claim to a particular usefulapplication, e.g., biometric identification and control systems andmethods for providing customizable security through authentication ofbiosignal representations of one or more user-specific and user-selectedgesture-intentions

Advantages will become more apparent to those of ordinary skill in theart from the following description of the preferred embodiments whichhave been shown and described by way of illustration. As will berealized, the present embodiments may be capable of other and differentembodiments, and their details are capable of modification in variousrespects. Accordingly, the drawings and description are to be regardedas illustrative in nature and not as restrictive.

BRIEF DESCRIPTION OF THE DRAWINGS

The Figures described below depict various aspects of the system andmethods disclosed therein. It should be understood that each Figuredepicts an embodiment of a particular aspect of the disclosed system andmethods, and that each of the Figures is intended to accord with apossible embodiment thereof. Further, wherever possible, the followingdescription refers to the reference numerals included in the followingFigures, in which features depicted in multiple Figures are designatedwith consistent reference numerals.

There are shown in the drawings arrangements which are presentlydiscussed, it being understood, however, that the present embodimentsare not limited to the precise arrangements and instrumentalities shown,wherein:

FIG. 1A illustrates a block diagram of an example biometricidentification and control system in accordance with various embodimentsherein.

FIG. 1B illustrates a flow diagram of an example biometricidentification and control method in accordance with various embodimentsherein.

FIG. 2A illustrates a first portion of a flow diagram of an examplegesture recording and authentication procedure as initiated byuser-specific and user-selected gesture-intentions and in accordancewith various embodiments herein.

FIG. 2B illustrates a second portion of the flow diagram of FIG. 2Aillustrating the example gesture recording and authentication procedureas initiated by user-specific and user-selected gesture-intentions andin accordance with various embodiments herein.

FIG. 3 illustrates examples of biometric signal data of a user.

FIG. 4 illustrates example user-specific and user-selectedgesture-intentions of a user.

FIG. 5 illustrates an example secure resource or device and auser-specific and user-selected gesture-intention performed to accessthe secure resource or device.

The Figures depict preferred embodiments for purposes of illustrationonly. Alternative embodiments of the systems and methods illustratedherein may be employed without departing from the principles of theinvention described herein.

DETAILED DESCRIPTION

While the present invention is susceptible of embodiment in manydifferent forms, there are shown in the drawings and will be describedherein in detail specific exemplary embodiments thereof, with theunderstanding that the present disclosure is to be considered as anexemplification of the principles of the invention and is not intendedto limit the invention to the specific embodiments illustrated. In thisrespect, before explaining at least one embodiment consistent with thepresent invention in detail, it is to be understood that the inventionis not limited in its application to the details of construction and tothe arrangements of components set forth above and below, illustrated inthe drawings, or as described in the examples. Methods and apparatusesconsistent with the present invention are capable of other embodimentsand of being practiced and carried out in various ways. Also, it is tobe understood that the phraseology and terminology employed herein, aswell as the abstract included below, are for the purposes of descriptionand should not be regarded as limiting.

FIG. 1A illustrates a block diagram of an example biometricidentification and control system 110 in accordance with variousembodiments herein. Biometric identification and control system 110 isconfigured to provide customizable security through authentication ofbiosignal representations of one or more user-specific and user-selectedgesture-intentions.

As illustrated by FIG. 1A, biometric identification and control system110 comprises a biometric detection device 112 configured to detectbiometric signals and/or data of a user 102. In various embodiments,biometric detection device 112 may comprise at least one of (a) one ormore electromyographic electrodes; (b) one or more electrocardiogramelectrodes; (c) one or more photodiodes; (d) one or more ultrasoundtransducers; (e) one or more accelerometers; (f) one or more gyroscopes;(g) one or more infrared sensors; or (h) one or more ultrasound sensors.Additionally, or alternatively, biometric detection device 112 may atleast be one of an implantable device (e.g., implanted on or within auser's body and/or skin); a wearable device (e.g., such as a watch, armband, leg band, etc.); or a remote detection device (e.g., such as aremote control or other device cable of sensing biometric signals of auser). Additionally, or alternatively, biometric detection device 112may be configured to be at least one of: subcutaneous positioned withrespect to the user, in contact with the user, implanted within theuser, and/or within a proximity to the user.

The biometric identification and control system 110 further comprises aprocessor 114 communicatively coupled to biometric detection device 112.Processor 114 may comprise a microprocessor, system on a chip (SoC), orprocessor, such as an ARM, ATOM, INTEL, or other similar processor(e.g., as typically used with wearable or similar devices) for executingcomputing instructions, applications, source code, or otherwise software(e.g., of software component) as depicted or described herein.

The biometric identification and control system 110 further comprises abiometric software component comprising computing instructionsexecutable by processor 114. The software component may be stored on amemory 116 communicatively coupled (e.g., via a SoC or computing bus) toprocessor 114.

Execution of the computing instructions of the software component byprocessor 114 causes processor 114 to perform an analysis of thebiometric signal data of the user as detected by biometric detectiondevice 112. For example, software component (e.g., stored in memory 116)may contain computing instructions executable by processor 114. Thecomputing instructions may be software implemented in a programminglanguage such as Java, C, C++, C#, Ruby, etc., and compiled to executeon processor 114 or may be otherwise be configured to be interpreted orrun by processor 114.

In various embodiments, computing instructions of the software component(e.g., stored in memory 116) may comprise a “while” loop executing toperform one or more portions of algorithms, methods, and/or flowdiagrams as described and/or illustrated for FIGS. 1B, 2A, and/or 2B orotherwise described herein. For example, the “while loop” may execute oroperate (e.g., via execution of processor 114) to detect and/or recordbiometric signal data of user 102 as detected and/or received bybiometric detection device 112. In such embodiments, detection and/orreceipt of the biometric signal data would result in a “true” conditionor state that would trigger the while loop to execute the one or moreportions or blocks of FIGS. 1B, 2A, and/or 2B or otherwise describedherein.

Additionally, or alternatively, computing instructions of the softwarecomponent (e.g., stored in memory 116) may comprise one or more eventlisteners, such as a listener function programmed to detect and/orreceive biometric signal data of user 102 as detected and/or received bybiometric detection device 112. In this way, biometric signals (e.g.,electromyographic (EMG)) of user 102 would be pushed to, or otherwisereceived by, biometric detection device 112 to detect or generate thebiometric signal data and trigger the listener function that would thenbe used by the one or more portions or blocks of FIGS. 1B, 2A, and/or 2Bor otherwise described herein.

In some embodiments biometric software component comprises an adaptivelearning component configured to identify or detect user-specific anduser-selected gesture-intention(s) (e.g., user-specific anduser-selected gesture-intentions 402, 404, 406 a, and/or 406 b asdescribed and illustrated by FIG. 4 herein) as performed by the user(e.g., user 102) and causing the generation of biometric signal data(e.g., biometric signal data 102 d) as detected for the user.

Additionally, or alternatively, biometric software component may furtherbe configured to use or modify biometric signal (e.g., user 102) data totrain or optimize the adaptive learning component for identification ordetection of the user-specific and user-selected gesture-intention.

As described herein, the adaptive learning component may be trainedusing a supervised or unsupervised machine learning program oralgorithm. The machine learning program or algorithm may employ a neuralnetwork, which may be a convolutional neural network, a deep learningneural network, or a combined learning module or program that learns intwo or more features or feature datasets in a particular areas ofinterest. The machine learning programs or algorithms may also includenatural language processing, semantic analysis, automatic reasoning,regression analysis, support vector machine (SVM) analysis, decisiontree analysis, random forest analysis, K-Nearest neighbor analysis,naïve Bayes analysis, clustering, reinforcement learning, and/or othermachine learning algorithms and/or techniques. Machine learning mayinvolve identifying and recognizing patterns in existing data (such asuser-specific and user-selected gesture-intentions as identified inpatterns of biometric signal data, e.g., biometric signal data 102 d) inorder to facilitate making predictions for subsequent data (to identifyor detect further user-specific and user-selected gesture-intentions asmade by the user for the purpose of providing authentication of the userfor access to a secure resource or device as described herein).

Machine learning model(s), such as those of adaptive learning component,may be created and trained based upon example (e.g., “training data,”)inputs or data (which may be termed “features” and “labels”) in order tomake valid and reliable predictions for new inputs, such as testinglevel or production level data or inputs. In supervised machinelearning, a machine learning program operating on a server, computingdevice, or otherwise processor(s), may be provided with example inputs(e.g., “features”) and their associated, or observed, outputs (e.g.,“labels”) in order for the machine learning program or algorithm todetermine or discover rules, relationships, or otherwise machinelearning “models” that map such inputs (e.g., “features”) to the outputs(e.g., labels), for example, by determining and/or assigning weights orother metrics to the model across its various feature categories. Suchrules, relationships, or otherwise models may then be providedsubsequent inputs in order for the model, executing on the server,computing device, or otherwise processor(s), to predict, based on thediscovered rules, relationships, or model, an expected output.

In unsupervised machine learning, the server, computing device, orotherwise processor(s), may be required to find its own structure inunlabeled example inputs, where, for example multiple trainingiterations are executed by the server, computing device, or otherwiseprocessor(s) to train multiple generations of models until asatisfactory model, e.g., a model that provides sufficient predictionaccuracy when given test level or production level data or inputs, isgenerated. The disclosures herein may use one or both of such supervisedor unsupervised machine learning techniques.

For example, in FIG. 1B, adaptive learning component may be loaded inmemory 116 and may be trained with biometric signal data 102 d torecognize user-specific and user-selected gesture-intentions (e.g.,user-specific and user-selected gesture-intentions 402, 404, 406 a,and/or 406 b). The adaptive learning component may then receive furtheror new biometric signal data 102 d, where biometric signals of user 102may be detected as a given user-specific and user-selectedgesture-intentions (e.g., user-specific and user-selectedgesture-intentions 402, 404, 406 a, and/or 406 b), which may then beused to provide authentication of the user for access to a secureresource or device as described herein.

Referring to FIG. 1B, execution of the computing instructions byprocessor 114 causes processor 114 to create a biometric profile basedon the analysis of the biometric signal data. In various embodiments,the biometric profile comprises an electronic recording of a biosignalrepresentation of a user-specific and user-selected gesture-intention ofthe user as described herein.

In addition, execution of the computing instructions by processor 114causes processor 114 to bind the user-specific and user-selectedgesture-intention of the user to a security interface as described andillustrated herein, e.g., for FIGS. 1A, 1B, 2A, and/or 2B or otherwiseherein. The security interface is operable to provide authentication ofthe user for access to a secure resource or device as described and/orillustrated herein, e.g., for FIGS. 1B, 2A, and/or 2B or otherwiseherein

In some embodiments, the biometric software component (e.g., stored inmemory 116) may comprises a user interface (e.g., a user interface 118)configured to receive one or more selections of the user for customizingthe security interface for operation in accordance with theuser-specific and user-selected gesture-intention. The user interfacemay comprise various kinds or types. For example, in some embodiments,the user interface may comprise a button user interface, such as adepressible and/or toggle button, that when pressed causes biometricidentification and control system 110 to operate in different modesand/or states (e.g., learning mode, gesture mode, etc.). For example,the learning mode may be toggled or selected when the user trainsbiometric identification and control system 110 to detect, record,and/or recognize one or more user-specific and user-selectedgesture-intentions of user 102 as described herein. Gesture mode may betoggled or selected when the user is ready to use or implement biometricidentification and control system 110 to detect and/or recognize one ormore user-specific and user-selected gesture-intentions of user 102 asdescribed herein.

Additionally, or alternatively, a user interface may comprise a virtualuser interface configured to display at least a portion of the biometricprofile. Such virtual user interface may comprise a graphic userinterface (GUI). Additionally, or alternatively, a virtual userinterface may comprise (a) a customized software command editingfunction, (b) a gesture calibration function, and/or (c) a biometricdetection apparatus manager. For example, the customized softwarecommand editing function may be rendered via a GUI or screen of thebiometric identification and control system 110 (e.g., on a wearabledevice such as a watch, arm band, etc.). The customized software commandediting function may allow a user (e.g., user 102) to edit parametersand/or configurations of the biometric identification and control system110 to control how and what actions that biometric identification andcontrol system 110 performs or takes when detecting biometric signaldata. This may include editing the types and/or number or gestures. Itmay also allow a user to a user to configure biometric identificationand control system 110 to operate and/or interface with various securityinterface(s) and/or secure resource(s) and/or device(s) as describedherein.

As an additional example, the gesture calibration function may berendered via a GUI or screen of the biometric identification and controlsystem 110 (e.g., on a wearable device such as a watch, arm band, etc.).The gesture calibration function may allow a user (e.g., user 102) totrain, set up, or otherwise configure biometric identification andcontrol system 110 to detect and/or recognize one or more user-specificand user-selected gesture-intentions of user 102 as described herein.

As a still further example, the biometric detection apparatus managermay be rendered via a GUI or screen of the biometric identification andcontrol system 110 (e.g., on a wearable device such as a watch, armband, etc.). The biometric detection apparatus manager may allow a user(e.g., user 102) to adjust the sensitivity of biometric detection device112 to control the detection sensitivity (e.g., the degree of when asignal is detected) and/or filtering of biometric signal data asreceived by user 102.

As illustrated for FIG. 1A, each of biometric detection device 112,processor 114, memory 116, and/or user interface 118 may becommunicatively coupled to one other via a computer, SoC interface,and/or other electronic interface.

In additional embodiments, biometric detection device 112, processor114, memory 116, and/or user interface 118 may be part of separatecomputing devices, which are communicatively coupled, e.g., via a wiredor wireless connection. For example, in one embodiment, user interface114 may be implemented on a separate or remote computing device (e.g., alaptop or computer) in wireless communication (e.g., BLUETOOTH or WIFI(802.11)) with biometric identification and control system 110, where auser configures the biometric identification and control system 110(e.g., by training or otherwise configuring the biometric softwarecomponent as described herein) via the remote user interface 114 on theseparate computing device. The biometric detection apparatus manager, orother software components, etc., may also be implemented or configuredon separate computing device in communication with biometricidentification and control system 110.

FIG. 1B illustrates a flow diagram of an example biometricidentification and control method 160 in accordance with variousembodiments herein. Biometric identification and control method 160illustrates customizable security through authentication of biosignalrepresentations of one or more user-specific and user-selectedgesture-intentions. In some embodiments, a tangible, non-transitorycomputer-readable medium may store instructions (e.g., in memory 116)for providing customizable security through authentication of biosignalrepresentations of one or more user-specific and user-selectedgesture-intentions. The instructions, when executed by one or moreprocessors, cause the one or more processors to execute the blocks orsteps as described for FIG. 1B.

With reference to FIG. 1B, biometric identification and control method160 comprises performing, by a biometric software component executing onprocessor 114 communicatively coupled to biometric detection device 112,an analysis of biometric signal data of a user (e.g., user 102 of FIG.1A) as detected by biometric detection device 112. In variouscomponents, software component may be stored in memory 116 and/orotherwise configured or set up as described for FIG. 1A or elsewhereherein. In various embodiments, biometric detection device 112 mayreceive raw signal data 102 r of user 102 and generate, transform, passthrough, identify, and/or otherwise detect biometric signal data 102 dfor analyzing by processor 114. Biometric detection device 112 maydetect raw signal data 102 r and/or biometric signal data 102 d of user102 as described herein for FIG. 1A.

In various embodiments biometric signal data 102 d may be analyzed withat least one of the following algorithms or computational techniques,including: (a) fuzzy logic; (b) pattern classification; (c)computational neural networks; (d) forward dynamic modelling; or (e)support vector machines. In various embodiments, such data analysis maycomprise creating at least one user-specific authentication key asdescribed herein. The user-specific authentication key is unique to auser-specific and user-selected gesture-intention of a user (e.g., user102).

With reference FIG. 1B, biometric identification and control method 160further comprises creating, by the biometric software component, abiometric profile based on the analysis of the biometric signal data. Invarious embodiments the biometric profile may be stored in memory 116.

In various embodiments, the biometric profile may comprise an electronicrecording of a biosignal representation of a user-specific anduser-selected gesture-intention of the user. Biometric profile maycomprise an electronic recording (e.g., as illustrated by FIG. 3) of abiosignal representation of a user-specific and user-selectedgesture-intention of the user. For example, the biosignal representationof a user-specific and user-selected gesture-intention of the user maybe defined by the biometric signal data 102 as detected for the user(e.g., user 102).

FIG. 3 illustrates examples of biometric signal data (e.g., idlebiometric signal data 102 d 1 and voluntary biometric signal data 102 d2) of a user (e.g., user 102). Such biometric signal data may be used todefine or otherwise represent a user-specific and user-selectedgesture-intention of the user. For example, the biometric signal dataillustrated by FIG. 3 may comprise biometric signal data 102 as detectedfor the user (e.g., user 102) as illustrated and/or described for FIGS.1A and/or 1B or elsewhere herein. In various embodiments, auser-specific and user-selected gesture-intention, or biometric signalsor data thereof, may comprise at least one of: eccentric contraction ofone or more muscles or muscle groups of a user (e.g., user 102);concentric contraction of one or more muscles or muscle groups of a user(e.g., user 102); and/or isometric contraction of one or more muscles ormuscle groups of the user (e.g., user 102). Such activity (e.g., anyoneone or more types of contraction of a muscle and/or muscle groups) maycause electromyographic (EMG) signals to be produced by user 102 thatmay be detected by biometric detection device 112 as described herein.

For example, FIG. 3, illustrates a comparative representation ofbiometric signal data 102 d (e.g., which is illustrated as EMG data—idlebiometric signal data 102 d 1 and voluntary biometric signal data 102 d2—as received by biometric detection device 112). In the example of FIG.3, diagram 300 illustrates biometric signal data 102 d 1 as received(over time 300 t), recorded, identified or as otherwise detected when auser (e.g., user 102) is at rest, i.e., is not performing a gesture orgesture intention, such as a user-specific and user-selectedgesture-intention as a described herein. Biometric signal data 102 d 1is detected over time 300 t at various signal strength 300 s, which as awhole, indicates a data pattern that defines a user-specific anduser-selected gesture-intention (or lack thereof as shown for theembodiment of diagram 300). Such biometric signal data (e.g., biometricsignal data 102 d 1) may be detected by biometric detection device 112as described herein.

Conversely, in the example of FIG. 3, diagram 350 illustrates biometricsignal data 102 d 2 as received (over time 350 t), recorded, identifiedor as otherwise detected when a user (e.g., user 102) is active, e.g.,is performing a gesture or gesture intention, such as a user-specificand user-selected gesture-intention as a described herein. Biometricsignal data 102 d 2 is detected over time 350 t at various signalstrength 350 s, which as a whole, indicates a data pattern that definesor represents a user-specific and user-selected gesture-intention (asshown for the embodiment of diagram 350). The data pattern, varyingacross time 350 t at different signal strengths, as shown for diagram350 of FIG. 3, uniquely defines the user-specific and user-selectedgesture-intention for the user (e.g., user 102). Such biometric signaldata (e.g., biometric signal data 102 d 2) may be detected by biometricdetection device 112 as described herein. In various embodiments, suchdata pattern may be used to generate, record, create, provide, orotherwise implement a given user-specific and user-selectedgesture-intention as described herein. In some embodiments, suchdetection of biometric signal data may cause a user-specificauthentication key to be provided to allow for security authenticationas provided herein.

FIG. 4 illustrates example user-specific and user-selectedgesture-intentions (e.g., user-specific and user-selectedgesture-intentions 402, 404, 406 a, and 406 b) of a user (e.g., user102). The user-specific and user-selected gesture-intentions (e.g.,user-specific and user-selected gesture-intentions 402, 404, 406 a, and406 b) of FIG. 4 illustrate several examples of voluntary gestures(e.g., a series of user-specific and user-selected gesture-intentions)that may be performed or implemented by user 102 to generate thebiometric signal data (e.g., biometric signal data 102 d 2 as describedfor FIG. 3). The various gestures, together and/or alone, generate orproduce different biometric patterns (e.g., biometric signal data 102 d2) that result in unique data signal that can be detected (e.g., bybiometric detection device 112) and that can be used to bind, drive, orotherwise setup commands, actions, or security interfaces, such asauthentication commands, actions, and/or security interfaces to provideto access secure resources or devices as described herein.

In the example of FIG. 4, a series of user-specific and user-selectedgesture-intentions, with alternatives or additions (e.g., gestures 406 aand 406 b) is illustrated. For example, such series begins withuser-specific and user-selected gesture-intention 402 in which user 102performs a pinch gesture with his or her hands and/or fingers. The pinchgesture performed by the user causes biometric signals (e.g., generatedby contraction of user 102's muscles or muscle groups as describedherein, such as muscles of the user's hand, finger, wrist, forearm,and/or other muscles) to be received and/or detected by biometricdetection device 112 of biometric identification and control system 110,which in the example of FIG. 4 is illustrated as implemented via awearable device (e.g., a watch based device).

Next, the series illustrated by FIG. 4 further comprises user-specificand user-selected gesture-intention 404 in which user 102 performs apoint gesture with his or her hand and/or fingers. The point gestureperformed by the user causes biometric signals (e.g., generated bycontraction of user 102's muscles or muscle groups as described herein,such as muscles of the user's hand, finger, wrist, forearm, and/or othermuscles) to be received and/or detected by biometric detection device112 of biometric identification and control system 110 (e.g., a watchbased device as shown in FIG. 4). The biometric signals generated forthe point gesture may be, and typically are, different from thosegenerated and detected for the previous pinch gesture.

Still further, the series illustrated by FIG. 4 further comprisesuser-specific and user-selected gesture-intention 406 a in which user102 performs a twirl gesture with his or her hand and/or fingers. Thetwirl gesture performed by the user causes biometric signals (e.g.,generated by contraction of user 102's muscles or muscle groups asdescribed herein, such as muscles of the user's hand, finger, wrist,forearm, and/or other muscles) to be received and/or detected bybiometric detection device 112 of biometric identification and controlsystem 110 (e.g., a watch based device as shown in FIG. 4). Thebiometric signals generated for the twirl gesture may be, and typicallyare, different from those generated and detected for the previous pinchand/or point gesture(s).

Additionally, or alternatively, the series illustrated by FIG. 4 furthercomprises user-specific and user-selected gesture-intention 406 b inwhich user 102 performs a lift gesture with his or her hand and/orfingers. The lift gesture performed by the user causes biometric signals(e.g., generated by contraction of user 102's muscles or muscle groupsas described herein, such as muscles of the user's hand, finger, wrist,forearm, and/or other muscles) to be received and/or detected bybiometric detection device 112 of biometric identification and controlsystem 110 (e.g., a watch based device as shown in FIG. 4). Thebiometric signals generated for the lift gesture may be, and typicallyare, different from those generated and detected for the previous pinch,point, and/or twirl gesture(s).

Any one or more of the user-specific and user-selectedgesture-intentions (e.g., any one or more of user-specific anduser-selected gesture-intentions 402, 404, 406 a, and/or 406 b) maycomprise a user-specific and user-selected gesture-intention, eithersingularly or as a whole, for binding to a security interface and/or toprovide authentication of the user for access to a secure resource ordevice as described herein. That is, in some embodiments only a singleuser-specific and user-selected gesture-intention may be implemented tocomprise a given user-specific and user-selected gesture-intention forsecurity access purposes as described herein. In other embodiments, asequence of user-specific and user-selected gesture-intentions may beimplemented to comprise a given user-specific and user-selectedgesture-intention for security access purposes as described herein. Forexample, where a sequence is implemented, the electronic recording ofthe biometric profile may further define a second user-specific anduser-selected gesture-intention of the user. The second user-specificand user-selected gesture-intention may be recorded in a sequence with afirst user-specific and user-selected gesture-intention of the user.Such a sequence may be bound to the security interface (e.g., securityinterface 134). In various embodiments, the sequence may be required orimplemented to provide authentication of the user for access to a secureresource or device (e.g., secure resource or device 136) as describedherein.

For example, with reference to FIG. 4, in some embodiments, the liftgesture of user-specific and user-selected gesture-intention 406 b maybe used separately from the twirl gesture of user-specific anduser-selected gesture-intention 406 a, in which only user-specific anduser-selected gesture-intentions 402, 404, and 406 a together, as awhole or in a sequence, comprise a comprehensive user-specific anduser-selected gesture-intention used to bind to a security interfaceand/or to provide authentication of a user for access to a secureresource or device as described herein. In other embodiments, the liftgesture of user-specific and user-selected gesture-intention 406 b maybe part of (and may follow) the twirl gesture of user-specific anduser-selected gesture-intention 406 a, in which all user-specific anduser-selected gesture-intentions 402, 404, 406 a, and 406 b together, asa whole and in a sequence, comprise a comprehensive user-specific anduser-selected gesture-intention used to bind to a security interfaceand/or to provide authentication of a user for access to a secureresource or device as described herein.

It is to be understood that the gestures as illustrated by FIG. 4 aremerely a subset of examples and that any one or more gestures,movements, or actions performed by the user (e.g., user 102) thatgenerate biometric signals (e.g., EMG signals) may be used to generatebiometrical signal data for use by the biometric identification andcontrol systems and method described herein. In addition, it is to beunderstood that one gesture or a series of gestures (e.g., asillustrated for Example 4) may be used to define a user-specific anduser-selected gesture-intention as described herein.

In some embodiments, a user-specific and user-selected gesture-intentionmay be predefined. In such embodiments, a user-specific anduser-selected gesture-intention (e.g., any of user-specific anduser-selected gesture-intentions 402, 404, 406 a, and/or 406 b asdescribed for FIG. 4) may be defined by a list of one or morepredetermined gestures as provided to the user to select from. Forexample, such a list may be displayed via user interface 118 ofbiometric identification and control system 110. The list may also bedisplayed on another user interface (such as a graphic user interface(GUI)) of a computing device having a processor and communicationinterface (e.g., a laptop, computer, etc. communicatively coupled via aBLUETOOTH or WIFI interface) to biometric identification and controlsystem 110.

Additionally, or alternatively, a user-specific and user-selectedgesture-intention (e.g., any of user-specific and user-selectedgesture-intentions 402, 404, 406 a, and/or 406 b as described for FIG.4) may be defined by one or more unique gestures or gesture intentionsas defined by the user. For example, FIG. 4 illustrates, at least insome embodiments, one or more of user-selected gesture-intentions 402,404, 406 a, and/or 406 b that may be unique gestures or gestureintentions as defined by or otherwise chosen by user 102.

In some embodiments, a user-specific and user-selected gesture-intentionmay comprise an actuated gesture that is a resulting physical responseof the user initiated upon performance of the user-specific anduser-selected gesture-intention. For example, such actuated gesture mayinclude a reflex of user 102, such as a natural reflex, brought on by aprevious gesture such that the actuated gesture is the natural orlearned next gesture that flows or follows a previous gesture. This caninclude a pinch gesture followed by a pinch out or pinch in gesture.Another example includes a thumb-up gesture followed by a relaxing ofthe thumb gesture. Still further, another example may include a pointgesture followed by a retracting gesture, where user 102 points his orher finger in a first gesture and where the actuated gesture is aretracting gesture where the finger returns to a state of rest followingthe point gesture.

In some embodiments, certain user gestures may be filtered or otherwiseignored. This allows biometric identification and control system 110 tostreamline or otherwise filter biometric signal data 102 d, which canimprove or better the efficiency of analysis by processor 114 byremoving unwanted or unused biometric signal data. In some embodiments,user gestures as represented by a user's biosignal representation may bestored in a user's biometric profile for filtering or otherwiseignoring. For example, in some embodiments, a biometric profile of auser (e.g., user 102) may further comprise a second electronic recordingof a second biosignal representation of a second user-specific anduser-selected gesture-intention of the user. The second electronicrecording and its corresponding second user-specific and user-selectedgesture-intention of the user may be second to a primary or firstelectronic recording and its corresponding primary or firstuser-specific and user-selected gesture-intention of the user used tobind to a security interface and/or to provide authentication of a userfor access to a secure resource or device as described herein. In suchembodiments, in order to filter or otherwise ignore the seconduser-specific and user-selected gesture-intention, the seconduser-specific and user-selected gesture-intention may be at least oneof: (1) deliberately not bound to the security interface (as describedherein), or (2) filtered by processor 114 to prevent access to thesecure resource or device as described herein.

In some embodiments, a biometric profile, as described herein, furthermay comprise a user-specific authentication key. A user-specificauthentication key may comprise or be based on a digital representationof biometric data of a user, such as biometric signal data 102,including, for example, 102 d 1 and/or voluntary biometric signal data102 d 2, and/or combinations thereof, as shown and described herein forFIG. 3 or otherwise herein. In other embodiments, user-specificauthentication key may be a cryptographic key generated based on thebiometric data of a user, such as biometric signal data 102, including,for example, 102 d 1 and/or voluntary biometric signal data 102 d 2,and/or combinations thereof.

In some embodiments, the biometric signal data may be used as a seedvalue (e.g., a random seed value) to generate or create theuser-specific authentication key as a cryptographic key. In suchembodiments, the user-specific authentication key may be generated withthe biometric signal data using an encryption algorithm, such as an RSAsecurity algorithm, MD5 encryption algorithm, HMAC encryption algorithm,or the like.

In various embodiments, the user-specific authentication key may begenerated and/or provided when a user (e.g., user 102) performs auser-specific and user-selected gesture-intention as described herein.For example, a user-specific authentication key may be generated when auser trains or updates biometric detection device 112 to learn a newuser-specific and user-selected gesture-intention. Additionally, oralternatively, a user-specific authentication key, as already trained,may be provided (e.g., from biometric profile and/or memory 116) when auser performs an existing user-specific and user-selectedgesture-intention. In various embodiments, the user-specificauthentication key may authorize the user to access to the secureresource or device as described herein.

As shown in the embodiment of FIG. 1B, biometric identification andcontrol method 160 comprises processor 114 that analyzes biometricsignal data 102 d to detect user-specific and user-selectedgesture-intention(s) as described herein. In some embodiments, thedetected user-specific and user-selected gesture-intention(s) may bestored in memory 116 (e.g., such as stored in or as part of a biometricprofile of a user (user 102) as described herein). In other embodiments,processor 114 may access memory 114 to load or otherwise access aprerecorded or existing user-specific and user-selectedgesture-intention for authentication of a user for access to a secureresource or device as described herein.

At block 120, processor 114 may determine whether a biometric signaldata 102 d matches or is otherwise is representative of a known,trained, recorded, or existing user-specific and user-selectedgesture-intention. For example, the software component may comprise apattern recognition component to detect patterns among biometric signalsand thereby detect user-specific and user-selected gesture-intention(s)(e.g., user-specific and user-selected gesture-intentions 402, 404, 406a, and/or 406 b). Such determination may include recognition of avoluntary biometric signal data pattern, e.g., such as voluntarybiometric signal data 102 d 2. If no such voluntary biometric datapattern is recognized or detected, then biometric identification andcontrol method 160 may end (at block 122) for a given iteration, wherean iteration comprises receipt of one or more biometric signals, e.g.,biometric signal data 102 d.

If a voluntary biometric data pattern is recognized or detected at block120, and matched with an existing or recorded user-specific anduser-selected gesture-intention, then biometric identification andcontrol method 160 continues to block 130 for the given iteration, Aniteration comprises receipt of one or more biometric signals, e.g.,biometric signal data 102 d, at biometric detection device 112. At block130, an authentication procedure that may be performed by processor 114.In various embodiment, the authentication procedure (at block 130) maycomprise determining whether a user-specific and user-selectedgesture-intention matches, is similar to, or is otherwise representativeof a known, trained, recorded, or existing user-specific anduser-selected gesture-intention. Once matched or identified, thespecific and user-selected gesture-intention may provide authenticationfor the user (e.g., user 102). For example, in various embodiments,authentication of a user-specific and user-selected gesture-intentionmay comprise: (a) collecting a first set of user biometric data (e.g.,biometric signal data 102 d) of the user during a first iteration, andcreating a biometric profile (e.g., as stored in memory 116)corresponding to the user-specific and user-selected gesture-intention;(b) collecting a second set of biometric data (e.g., biometric signaldata 102 d) of the user during a second iteration; and (c)authenticating (at block 130) that the biometric signals of the secondset of user biometric data has a similarity with (or otherwise matchesor is representative of) the first set of biometric data of thebiometric profile. Similarity may be determined based on a providedthreshold or tolerance, where the threshold or tolerance is a numericalvalue that defines a difference in signal strength overtime time (e.g.,as illustrated for FIG. 3, e.g., voluntary biometric signal data 102 d2) that the second set of biometric data may differ from the first setof biometric data in order for an identification, match, detection, orotherwise recognition of the user-specific and user-selectedgesture-intention to occur. Such threshold or tolerance may be definedin terms of signal strength such as voltage, amperes (amps), or othersignal values of numerical type or quantity.

At block 132, processor 114 determines whether a given user-specific anduser-selected gesture-intention (e.g., as performed by user 102) isauthenticated. If a given user-specific and user-selectedgesture-intention is not authenticated, then biometric identificationand control method 160 may end (at block 122) for a given iteration,where an iteration comprises receipt of one or more biometric signals,e.g., biometric signal data 102 d.

If a given user-specific and user-selected gesture-intention isauthenticated, then biometric identification and control method 160continues for a given iteration, where an iteration comprises receipt ofone or more biometric signals, e.g., biometric signal data 102 d.

With reference to FIG. 1B, biometric identification and control method160 further comprises binding, by the biometric software component, auser-specific and user-selected gesture-intention of the user to asecurity interface 134. Security interface 134 is operable to provideauthentication of the user (e.g., user 102) for access to a secureresource or device (e.g., a locked device, such as a physical lock or avirtual lock implemented as part of a physical and/or virtual securityunit, system, platform, etc. such as described for FIG. 5 herein).

For example, in various embodiments, user-specific and user-selectedgesture-intention(s) (e.g., user-specific and user-selectedgesture-intentions 402, 404, 406 a, and/or 406 b) of a user (e.g., user102)) may each, together or alone, and/or in various combinations, bebound to security interface 134. Once bound to security interface 134, auser may implement any of the one or more user-specific anduser-selected gesture-intention(s) (e.g., user-specific anduser-selected gesture-intentions 402, 404, 406 a, and/or 406 b) toaccess or otherwise interact with a secure resource or device 136.

In some embodiments, biometric identification and control method 160 maycomprise linking a function of secure resource or device 136 to one ormore user-specific and user-selected gesture-intention(s) (e.g.,user-specific and user-selected gesture-intentions 402, 404, 406 a,and/or 406 b) thereby binding such one or more user-specific anduser-selected gesture-intention(s) to security interface 134 and secureresource or device 136. In such embodiments, the linking function isconfigured to execute upon the user initiating the user-specific anduser-selected gesture-intention.

In various embodiments herein, security interface 134 comprises anapplication programming interface (API) that may include source codeand/or hardware for communicating or otherwise interacting with (e.g.,via wired or wireless communication) secure resource or device 136. Insome embodiments, secure resource or device 136 may have a separate APIor interface as provided by a manufacturer or provider (e.g., thirdparty) of secure resource or device 136. In such embodiments, securityinterface 134 may interface or interact with (e.g., via BLUETOOTH, WIFI,USB connection, or otherwise) secure resource or device 136 to accesssecure resource or device 136.

In some embodiments, by way of non-limiting example, a secure resourceor device 136 may comprise a physical lock (e.g., a lock of door, suchas a building or home door, or door of a vehicle, or other such asset)wherein a function that is linked comprises locking or unlocking thephysical lock. The function may be linked or bound to a user-specificand user-selected gesture-intention (e.g., user-specific anduser-selected gesture-intentions 402, 404, 406 a, and/or 406 b) viasecurity interface 134 as described herein.

In additional embodiments, for example, a secure resource or device 136may comprise a mechanically automated process (e.g., opening of a garagedoor via interaction with a garage door opener) wherein the functionthat is linked comprises controlling or accessing the mechanicallyautomated process. The function may be linked or bound to auser-specific and user-selected gesture-intention (e.g., user-specificand user-selected gesture-intentions 402, 404, 406 a, and/or 406 b) viasecurity interface 134 as described herein.

In still further embodiments, for example, a secure resource or device136 may comprise a hardware component (e.g., a lock box that has an APIfor receiving a wireless unlock signal) and wherein the functioncomprises controlling or accessing the hardware component. The functionmay be linked or bound to a user-specific and user-selectedgesture-intention (e.g., user-specific and user-selectedgesture-intentions 402, 404, 406 a, and/or 406 b) via security interface134 as described herein.

In still further embodiments, for example, a secure resource or device136 may comprise a software program having a lock screen or secure dataand wherein the function comprises initiating or accessing the softwareprogram. The function may be linked or bound to a user-specific anduser-selected gesture-intention (e.g., user-specific and user-selectedgesture-intentions 402, 404, 406 a, and/or 406 b) via security interface134 as described herein.

FIG. 5 illustrates an example secure resource or device 136 (e.g., aphysical lock or representation of a virtual lock of a computingresource or device) and a user-specific and user-selectedgesture-intention (okay gesture 512) performed to access the secureresource or device 136. User hand 502 illustrates a user's hand (e.g.,of user 102) at rest. Biometric signals of the user (e.g., user 102) arereceived or detected by biometric detection device 112 of biometricidentification and control system 110, whereby biometric signal data 102d is determined and analyzed as described herein. Biometric signal data102 d 1 of FIG. 3 is representative of biometric data generated by userhand 502. Biometric identification and control system 110 is depicted inFIG. 5 as a wearable device (e.g., a watch or arm band). In addition,biometric identification and control system of FIG. 10 iscommunicatively coupled to secure resource or device 136 via a wirelessconnection 520 (e.g., BLUETOOTH or WIFI (802.11 standard)). Throughwireless connection 520, the biometric signals can be transmitted tosecure resource or device 136 (e.g., a physical lock or representationof a virtual lock of a computing resource or device) via securityinterface 134 as described herein.

As shown for FIG. 5, user hand 512 illustrates the user's hand (e.g., ofuser 102) during an okay gesture 512. Biometric signals of the user(e.g., user 102), during okay gesture 512, are received or detected bybiometric detection device 112 of biometric identification and controlsystem 110, whereby biometric signal data 102 d is determined andanalyzed as described herein. Biometric signal data 102 d 2 of FIG. 3 isrepresentative of biometric data generated by user hand 512. Throughwireless connection 520, the biometric signals, as generated by theuser's okay gesture 512, are transmitted to secure resource or device136 (e.g., a physical lock or representation of a virtual lock of acomputing resource or device) via security interface 134 as describedherein. In the embodiment of FIG. 5, the okay gesture 512 unlocks secureresource or device 136 to place secure resource or device 136 inunlocked state 136 a. Accordingly, in the embodiment of FIG. 5,biometric identification and control system 110 has previously beentrained or otherwise configured (e.g., by recording and storing okaygesture 512) to recognize or detect a given user-specific anduser-selected gesture-intention (okay gesture 512) and that gesture isbound to security interface 134 for unlocking secure resource or device136 (e.g., the physical lock or representation of a virtual lock of acomputing resource or device).

In various embodiments, secure resource or device 136 may be a deviceprovided by a third party company, such as a lock of door that locked orunlocked via security interface 134. In such embodiments, performance ofthe given user-specific and user-selected gesture-intention (okaygesture 512) may unlock the door and provide access to a room, house,building, area, vehicle, or other physical object or asset. In otherembodiments, secure resource or device 136 may be a virtual lock, suchas a lock screen on a mobile device or computer screen, wherebyperformance of the given user-specific and user-selectedgesture-intention (okay gesture 512) may unlock and provide access tosoftware, screens, or other virtual or computing resources on acomputing device, GUI, or other software resources or assets.

FIG. 2A illustrates a first portion 200 of a flow diagram of an examplegesture recording and authentication procedure as initiated byuser-specific and user-selected gesture-intentions and in accordancewith various embodiments herein. FIG. 2A illustrates a first iterationof biometric identification and control system 110 receiving a first setof biometric signal data 102 d. As shown for FIG. 2A, user 102 sends acommand to user-interface 118 to initiate a calibration procedure 121.User-interface 118 may be a button interface or a virtual interface asdescribed herein. Calibration procedure then prompts or otherwise allowsa user 102 to perform a user-specific and user-selectedgesture-intention (e.g., any of user-specific and user-selectedgesture-intentions 402, 404, 406 a, and/or 406 b as described andillustrated by FIG. 4 herein) for recording. Biometric detection device112 receives and detects the user's biometric signal data 102 d of user102, which is recorded, and analyzed by processor 114. Memory 116 maythen store the biometric signal pattern for the related user-specificand user-selected gesture-intention. The stored or otherwise recordeduser-specific and user-selected gesture-intention may then beimplemented or used as described in FIG. 2B.

FIG. 2B illustrates a second portion 250 of the flow diagram of FIG. 2Aillustrating the example gesture recording and authentication procedureas initiated by user-specific and user-selected gesture-intentions andin accordance with various embodiments herein. FIG. 2B illustrates asecond iteration of biometric identification and control system 110receiving a second set of biometric signal data 102 d. As shown for FIG.2B, biometric detection device 112 receives and detects the user'sbiometric signal data 102 d of user 102, which may be recorded, andanalyzed by processor 114. Biometric identification and control system110 may then implement authentication procedure 130 as described herein.In some embodiments, as shown for FIG. 2B, processor 114 may accessmemory 116 to compare biometric signal data 102 d to existing (stored)data patterns or signals of one or more user-specific and user-selectedgesture-intention(s) (e.g., any of user-specific and user-selectedgesture-intentions 402, 404, 406 a, and/or 406 b as described andillustrated by FIG. 4 herein). If there is no biometric signal patternmatch (130 n), then security interface 134 is not invoked or otherwiseaccessed, and the current iteration, for the currently receivedbiometric signal data 102 d, ends (122). However, if there is abiometric signal pattern match (130 m), then security interface 134 isinvoked or otherwise accessed, and, for the current iteration, i.e., forthe currently received biometric signal data 102 d, the securityinterface 134 provides authentication of the user for access to a secureresource or device (e.g., secure resource or device 136) as describedherein.

Aspects of the Present Disclosure

The following aspects of the disclosure are exemplary only and notintended to limit the scope of the disclosure.

1. A biometric identification and control system configured to providecustomizable security through authentication of biosignalrepresentations of one or more user-specific and user-selectedgesture-intentions, the biometric identification and control systemcomprising: a biometric detection device configured to detect biometricsignal data of a user; a processor communicatively coupled to thebiometric detection device; and a biometric software componentcomprising computing instructions executable by the processor, whereinexecution of the computing instructions by the processor causes theprocessor to: perform an analysis of the biometric signal data of theuser as detected by the biometric detection device, create a biometricprofile based on the analysis of the biometric signal data, thebiometric profile comprising an electronic recording of a biosignalrepresentation of a user-specific and user-selected gesture-intention ofthe user, and bind the user-specific and user-selected gesture-intentionof the user to a security interface, wherein the security interface isoperable to provide authentication of the user for access to a secureresource or device.

2. The biometric and identification control system of aspect 1, whereinthe biometric software component comprises a user interface configuredto receive one or more selections of the user for customizing thesecurity interface for operation in accordance with the user-specificand user-selected gesture-intention.

3. The biometric and identification control system of aspect 2, whereinthe user interface comprises at least one of: (1) a button userinterface, or (2) a virtual user interface configured to display atleast a portion of the biometric profile, wherein the biometric profilefurther comprises at least one of: (a) a customized software commandediting function, (b) a gesture calibration function, or (c) a biometricdetection apparatus manager.

4. The biometric and identification control system of any one of aspects1-3, wherein the authentication of the user-specific and user-selectedgesture-intention comprises: (a) collecting a first set of userbiometric data of the user, and creating a biometric profilecorresponding to the user-specific and user-selected gesture-intention;(b) collecting a second set of biometric data of the user; and (c)authenticating that the biometric signals of the second set of userbiometric data has a similarity with the first set of biometric data ofthe biometric profile.

5. The biometric and identification control system of any one of aspects1-4, wherein the user-specific and user-selected gesture-intentioncomprises at least one of: eccentric contraction of one or more musclesor muscle groups of the user; concentric contraction of one or moremuscles or muscle groups of the user; or isometric contraction of one ormore muscles or muscle groups of the user.

6. The biometric and identification control system of any one of aspects1-5, wherein the biometric detection device comprises at least one of(a) one or more electromyographic electrodes; (b) one or moreelectrocardiogram electrodes; (c) one or more photodiodes; (d) one ormore ultrasound transducers; (e) one or more accelerometers; (f) one ormore gyroscopes; (g) one or more infrared sensors; or (h) one or moreultrasound sensors.

7. The biometric and identification control system of any one of aspects1-6, wherein the analysis of the biometric signal data of the usercomprises data analysis of the biometric signal data with at least oneof: (a) fuzzy logic; (b) pattern classification; (c) computationalneural networks; (d) forward dynamic modelling; or (e) support vectormachines, and wherein the data analysis comprises creating at least oneuser-specific authentication key that is unique to the user-specific anduser-selected gesture-intention of the user.

8. The biometric and identification control system of aspect 7, whereinthe biometric profile further comprises the user-specific authenticationkey.

9. The biometric and identification control system of aspect 7, whereinthe user-specific authentication key is generated or provided when theuser performs the user-specific and user-selected gesture-intention, andwherein the user-specific authentication key authorizes the user toaccess to the secure resource or device.

10. The biometric and identification control system of any one ofaspects 1-9 further comprising linking a function of the secure resourceor device to the user-specific and user-selected gesture-intention,wherein the function is configured to execute upon the user initiatingthe user-specific and user-selected gesture-intention.

11. The biometric and identification control system of aspect 10,wherein the secure resource or device comprises at least one of: aphysical lock wherein the function that is linked comprises locking orunlocking the physical lock; a mechanically automated process whereinthe function that is linked comprises controlling or accessing themechanically automated process; a hardware component and wherein thefunction comprises controlling or accessing the hardware component; or asoftware program and wherein the function comprises initiating oraccessing the software program.

12. The biometric and identification control system of any one ofaspects 1-11, wherein the user-specific and user-selectedgesture-intention is defined by at least one of: (1) a list of one ormore predetermined gestures as provided to the user to select from; or(2) one or more unique gestures or gesture intentions as defined by theuser.

13. The biometric and identification control system of any one ofaspects 1-12, wherein the biometric detection device comprises at leastone of: an implantable device, a wearable device, or a remote detectiondevice.

14. The biometric and identification control system of any one ofaspects 1-13, wherein the biometric software component comprises anadaptive learning component configured to identify the user-specific anduser-selected gesture-intention performed by the user based on thebiometric signal data as detected for the user.

15. The biometric and identification control system of any one of aspect1-14, wherein the biometric software component comprises a patternrecognition component.

16. The biometric and identification control system of aspect 14,wherein the biometric software component is further configured to modifythe biometric signal data to optimize the adaptive learning componentfor identification of the user-specific and user-selectedgesture-intention.

17. The biometric identification and control system of any one ofaspects 1-16, wherein the electronic recording of the biometric profilefurther defines a second user-specific and user-selectedgesture-intention of the user, wherein the second user-specific anduser-selected gesture-intention is recorded in a sequence with theuser-specific and user-selected gesture-intention of the user, andwherein the sequence is bound to the security interface, and wherein thesequence is required to provide authentication of the user for access tothe secure resource or device.

18. The biometric identification and control system of any one ofaspects 1-17, wherein the user-specific and user-selectedgesture-intention comprises an actuated gesture that is a resultingphysical response of the user initiated upon performance of theuser-specific and user-selected gesture-intention.

19. The biometric identification and control system of any one ofaspects 1-18, wherein the biometric detection device is furtherconfigured to be at least one of: subcutaneous positioned with respectto the user, in contact with the user, implanted within the user, orwithin a proximity to the user.

20. The biometric identification and control system of any one ofaspects 1-19, wherein the biometric profile further comprises a secondelectronic recording of a second biosignal representation of a seconduser-specific and user-selected gesture-intention of the user, whereinthe second user-specific and user-selected gesture-intention is at leastone of: (1) deliberately not bound to the security interface, or (2)filtered by the processor to prevent access to the secure resource ordevice.

21. A biometric identification and control method for providingcustomizable security through authentication of biosignalrepresentations of one or more user-specific and user-selectedgesture-intentions, the biometric identification and control methodcomprising: performing, by a biometric software component executed by aprocessor communicatively coupled to a biometric detection device, ananalysis of biometric signal data of a user as detected by the biometricdetection device; creating, by the biometric software component, abiometric profile based on the analysis of the biometric signal data,the biometric profile comprising an electronic recording of a biosignalrepresentation of a user-specific and user-selected gesture-intention ofthe user; and binding, by the biometric software component, theuser-specific and user-selected gesture-intention of the user to asecurity interface, wherein the security interface is operable toprovide authentication of the user for access to a secure resource ordevice.

22. A tangible, non-transitory computer-readable medium storinginstructions for providing customizable security through authenticationof biosignal representations of one or more user-specific anduser-selected gesture-intentions, that when executed by one or moreprocessors cause the one or more processors to: perform, by a biometricsoftware component executed by a processor communicatively coupled to abiometric detection device, an analysis of biometric signal data of auser as detected by the biometric detection device; create, by thebiometric software component, a biometric profile based on the analysisof the biometric signal data, the biometric profile comprising anelectronic recording of a biosignal representation of a user-specificand user-selected gesture-intention of the user; and bind, by thebiometric software component, the user-specific and user-selectedgesture-intention of the user to a security interface, wherein thesecurity interface is operable to provide authentication of the user foraccess to a secure resource or device.

Additional Considerations

Although the disclosure herein sets forth a detailed description ofnumerous different embodiments, it should be understood that the legalscope of the description is defined by the words of the claims set forthat the end of this patent and equivalents. The detailed description isto be construed as exemplary only and does not describe every possibleembodiment since describing every possible embodiment would beimpractical. Numerous alternative embodiments may be implemented, usingeither current technology or technology developed after the filing dateof this patent, which would still fall within the scope of the claims.

The following additional considerations apply to the foregoingdiscussion. Throughout this specification, plural instances mayimplement components, operations, or structures described as a singleinstance. Although individual operations of one or more methods areillustrated and described as separate operations, one or more of theindividual operations may be performed concurrently, and nothingrequires that the operations be performed in the order illustrated.Structures and functionality presented as separate components in exampleconfigurations may be implemented as a combined structure or component.Similarly, structures and functionality presented as a single componentmay be implemented as separate components. These and other variations,modifications, additions, and improvements fall within the scope of thesubject matter herein.

Additionally, certain embodiments are described herein as includinglogic or a number of routines, subroutines, applications, orinstructions. These may constitute either software (e.g., code embodiedon a machine-readable medium or in a transmission signal) or hardware.In hardware, the routines, etc., are tangible units capable ofperforming certain operations and may be configured or arranged in acertain manner. In example embodiments, one or more computer systems(e.g., a standalone, client or server computer system) or one or morehardware modules of a computer system (e.g., a processor or a group ofprocessors) may be configured by software (e.g., an application orapplication portion) as a hardware module that operates to performcertain operations as described herein.

In various embodiments, a hardware module may be implementedmechanically or electronically. For example, a hardware module maycomprise dedicated circuitry or logic that is permanently configured(e.g., as a special-purpose processor, such as a field programmable gatearray (FPGA) or an application-specific integrated circuit (ASIC)) toperform certain operations. A hardware module may also compriseprogrammable logic or circuitry (e.g., as encompassed within ageneral-purpose processor or other programmable processor) that istemporarily configured by software to perform certain operations. Itwill be appreciated that the decision to implement a hardware modulemechanically, in dedicated and permanently configured circuitry, or intemporarily configured circuitry (e.g., configured by software) may bedriven by cost and time considerations.

Accordingly, the term “hardware module” should be understood toencompass a tangible entity, be that an entity that is physicallyconstructed, permanently configured (e.g., hardwired), or temporarilyconfigured (e.g., programmed) to operate in a certain manner or toperform certain operations described herein. Considering embodiments inwhich hardware modules are temporarily configured (e.g., programmed),each of the hardware modules need not be configured or instantiated atany one instance in time. For example, where the hardware modulescomprise a general-purpose processor configured using software, thegeneral-purpose processor may be configured as respective differenthardware modules at different times. Software may accordingly configurea processor, for example, to constitute a particular hardware module atone instance of time and to constitute a different hardware module at adifferent instance of time.

Hardware modules may provide information to, and receive informationfrom, other hardware modules. Accordingly, the described hardwaremodules may be regarded as being communicatively coupled. Where multipleof such hardware modules exist contemporaneously, communications may beachieved through signal transmission (e.g., over appropriate circuitsand buses) that connect the hardware modules. In embodiments in whichmultiple hardware modules are configured or instantiated at differenttimes, communications between such hardware modules may be achieved, forexample, through the storage and retrieval of information in memorystructures to which the multiple hardware modules have access. Forexample, one hardware module may perform an operation and store theoutput of that operation in a memory device to which it iscommunicatively coupled. A further hardware module may then, at a latertime, access the memory device to retrieve and process the storedoutput. Hardware modules may also initiate communications with input oroutput devices, and may operate on a resource (e.g., a collection ofinformation).

The various operations of example methods described herein may beperformed, at least partially, by one or more processors that aretemporarily configured (e.g., by software) or permanently configured toperform the relevant operations. Whether temporarily or permanentlyconfigured, such processors may constitute processor-implemented modulesthat operate to perform one or more operations or functions. The modulesreferred to herein may, in some example embodiments, compriseprocessor-implemented modules.

Similarly, the methods or routines described herein may be at leastpartially processor-implemented. For example, at least some of theoperations of a method may be performed by one or more processors orprocessor-implemented hardware modules. The performance of certain ofthe operations may be distributed among the one or more processors, notonly residing within a single machine, but deployed across a number ofmachines. In some example embodiments, the processor or processors maybe located in a single location, while in other embodiments theprocessors may be distributed across a number of locations.

The performance of certain of the operations may be distributed amongthe one or more processors, not only residing within a single machine,but deployed across a number of machines. In some example embodiments,the one or more processors or processor-implemented modules may belocated in a single geographic location (e.g., within a homeenvironment, an office environment, or a server farm). In otherembodiments, the one or more processors or processor-implemented modulesmay be distributed across a number of geographic locations.

This detailed description is to be construed as exemplary only and doesnot describe every possible embodiment, as describing every possibleembodiment would be impractical, if not impossible. A person of ordinaryskill in the art may implement numerous alternate embodiments, usingeither current technology or technology developed after the filing dateof this application.

Those of ordinary skill in the art will recognize that a wide variety ofmodifications, alterations, and combinations can be made with respect tothe above described embodiments without departing from the scope of theinvention, and that such modifications, alterations, and combinationsare to be viewed as being within the ambit of the inventive concept.

The patent claims at the end of this patent application are not intendedto be construed under 35 U.S.C. § 112(f) unless traditionalmeans-plus-function language is expressly recited, such as “means for”or “step for” language being explicitly recited in the claim(s). Thesystems and methods described herein are directed to an improvement tocomputer functionality, and improve the functioning of conventionalcomputers.

What is claimed is:
 1. A biometric identification and control systemconfigured to provide customizable security through authentication ofbiosignal representations of one or more user-specific and user-selectedgesture-intentions, the biometric identification and control systemcomprising: a biometric detection device configured to detect biometricsignal data of a user; a processor communicatively coupled to thebiometric detection device; and a biometric software componentcomprising computing instructions executable by the processor, whereinexecution of the computing instructions by the processor causes theprocessor to: perform an analysis of the biometric signal data of theuser as detected by the biometric detection device, create a biometricprofile based on the analysis of the biometric signal data, thebiometric profile comprising an electronic recording of a biosignalrepresentation of a user-specific and user-selected gesture-intention ofthe user, and bind the user-specific and user-selected gesture-intentionof the user to a security interface, wherein the security interface isoperable to provide authentication of the user for access to a secureresource or device.
 2. The biometric and identification control systemof claim 1, wherein the biometric software component comprises a userinterface configured to receive one or more selections of the user forcustomizing the security interface for operation in accordance with theuser-specific and user-selected gesture-intention.
 3. The biometric andidentification control system of claim 2, wherein the user interfacecomprises at least one of: (1) a button user interface, or (2) a virtualuser interface configured to display at least a portion of the biometricprofile, wherein the biometric profile further comprises at least oneof: (a) a customized software command editing function, (b) a gesturecalibration function, or (c) a biometric detection apparatus manager. 4.The biometric and identification control system of claim 1, wherein theauthentication of the user-specific and user-selected gesture-intentioncomprises: (a) collecting a first set of user biometric data of theuser, and creating a biometric profile corresponding to theuser-specific and user-selected gesture-intention; (b) collecting asecond set of biometric data of the user; and (c) authenticating thatthe biometric signals of the second set of user biometric data has asimilarity with the first set of biometric data of the biometricprofile.
 5. The biometric and identification control system of claim 1,wherein the user-specific and user-selected gesture-intention comprisesat least one of: eccentric contraction of one or more muscles or musclegroups of the user; concentric contraction of one or more muscles ormuscle groups of the user; or isometric contraction of one or moremuscles or muscle groups of the user.
 6. The biometric andidentification control system of claim 1, wherein the biometricdetection device comprises at least one of (a) one or moreelectromyographic electrodes; (b) one or more electrocardiogramelectrodes; (c) one or more photodiodes; (d) one or more ultrasoundtransducers; (e) one or more accelerometers; (f) one or more gyroscopes;(g) one or more infrared sensors; or (h) one or more ultrasound sensors.7. The biometric and identification control system of claim 1, whereinthe analysis of the biometric signal data of the user comprises dataanalysis of the biometric signal data with at least one of: (a) fuzzylogic; (b) pattern classification; (c) computational neural networks;(d) forward dynamic modelling; or (e) support vector machines, andwherein the data analysis comprises creating at least one user-specificauthentication key that is unique to the user-specific and user-selectedgesture-intention of the user.
 8. The biometric and identificationcontrol system of claim 7, wherein the biometric profile furthercomprises the user-specific authentication key.
 9. The biometric andidentification control system of claim 7, wherein the user-specificauthentication key is generated or provided when the user performs theuser-specific and user-selected gesture-intention, and wherein theuser-specific authentication key authorizes the user to access to thesecure resource or device.
 10. The biometric and identification controlsystem of claim 1 further comprising linking a function of the secureresource or device to the user-specific and user-selectedgesture-intention, wherein the function is configured to execute uponthe user initiating the user-specific and user-selectedgesture-intention.
 11. The biometric and identification control systemof claim 10, wherein the secure resource or device comprises at leastone of: a physical lock wherein the function that is linked compriseslocking or unlocking the physical lock; a mechanically automated processwherein the function that is linked comprises controlling or accessingthe mechanically automated process; a hardware component and wherein thefunction comprises controlling or accessing the hardware component; or asoftware program and wherein the function comprises initiating oraccessing the software program.
 12. The biometric and identificationcontrol system of claim 1, wherein the user-specific and user-selectedgesture-intention is defined by at least one of: (1) a list of one ormore predetermined gestures as provided to the user to select from; or(2) one or more unique gestures or gesture intentions as defined by theuser.
 13. The biometric and identification control system of claim 1,wherein the biometric detection device comprises at least one of: animplantable device, a wearable device, or a remote detection device. 14.The biometric and identification control system of claim 1, wherein thebiometric software component comprises an adaptive learning componentconfigured to identify the user-specific and user-selectedgesture-intention performed by the user based on the biometric signaldata as detected for the user.
 15. The biometric and identificationcontrol system of claim 1, wherein the biometric software componentcomprises a pattern recognition component.
 16. The biometric andidentification control system of claim 14, wherein the biometricsoftware component is further configured to modify the biometric signaldata to optimize the adaptive learning component for identification ofthe user-specific and user-selected gesture-intention.
 17. The biometricidentification and control system of claim 1, wherein the electronicrecording of the biometric profile further defines a seconduser-specific and user-selected gesture-intention of the user, whereinthe second user-specific and user-selected gesture-intention is recordedin a sequence with the user-specific and user-selected gesture-intentionof the user, and wherein the sequence is bound to the securityinterface, and wherein the sequence is required to provideauthentication of the user for access to the secure resource or device.18. The biometric identification and control system of claim 1, whereinthe user-specific and user-selected gesture-intention comprises anactuated gesture that is a resulting physical response of the userinitiated upon performance of the user-specific and user-selectedgesture-intention.
 19. The biometric identification and control systemof claim 1, wherein the biometric detection device is further configuredto be at least one of: subcutaneous positioned with respect to the user,in contact with the user, implanted within the user, or within aproximity to the user.
 20. The biometric identification and controlsystem of claim 1, wherein the biometric profile further comprises asecond electronic recording of a second biosignal representation of asecond user-specific and user-selected gesture-intention of the user,wherein the second user-specific and user-selected gesture-intention isat least one of: (1) deliberately not bound to the security interface,or (2) filtered by the processor to prevent access to the secureresource or device.
 21. A biometric identification and control methodfor providing customizable security through authentication of biosignalrepresentations of one or more user-specific and user-selectedgesture-intentions, the biometric identification and control methodcomprising: performing, by a biometric software component executed by aprocessor communicatively coupled to a biometric detection device, ananalysis of biometric signal data of a user as detected by the biometricdetection device; creating, by the biometric software component, abiometric profile based on the analysis of the biometric signal data,the biometric profile comprising an electronic recording of a biosignalrepresentation of a user-specific and user-selected gesture-intention ofthe user; and binding, by the biometric software component, theuser-specific and user-selected gesture-intention of the user to asecurity interface, wherein the security interface is operable toprovide authentication of the user for access to a secure resource ordevice.
 22. A tangible, non-transitory computer-readable medium storinginstructions for providing customizable security through authenticationof biosignal representations of one or more user-specific anduser-selected gesture-intentions, that when executed by one or moreprocessors cause the one or more processors to: perform, by a biometricsoftware component executed by a processor communicatively coupled to abiometric detection device, an analysis of biometric signal data of auser as detected by the biometric detection device; create, by thebiometric software component, a biometric profile based on the analysisof the biometric signal data, the biometric profile comprising anelectronic recording of a biosignal representation of a user-specificand user-selected gesture-intention of the user; and bind, by thebiometric software component, the user-specific and user-selectedgesture-intention of the user to a security interface, wherein thesecurity interface is operable to provide authentication of the user foraccess to a secure resource or device.